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Updated: Dec 27, 2025

Characterization of Functionally Associated miRNAs in Glioblastoma and their Engineering into Artificial Clusters for Gene Therapy
Published on: October 4, 2019
Transcriptome analyses reveal molecular mechanisms underlying phenotypic differences among transcriptional subtypes
Yuan-Bo Pan1, Siqi Wang2,3, Biao Yang4
1Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Abstract:
Using molecular signatures, previous studies have defined glioblastoma (GBM) subtypes with different phenotypes, such as the proneural (PN), neural (NL), mesenchymal (MES) and classical (CL) subtypes. However, the gene programmes underlying the phenotypes of these subtypes were less known. We applied weighted gene co-expression network analysis to establish gene modules corresponding to various subtypes. RNA-seq and immunohistochemical data were used to validate the expression of identified genes. We identified seven molecular subtype-specific modules and several candidate signature genes for different subtypes. Next, we revealed, for the first time, that radioresistant/chemoresistant gene signatures exist only in the PN subtype, as described by Verhaak et al, but do not exist in the PN subtype described by Phillips et al PN subtype. Moreover, we revealed that the tumour cells in the MES subtype GBMs are under ER stress and that angiogenesis and the immune inflammatory response are both significantly elevated in this subtype. The molecular basis of these biological processes was also uncovered. Genes associated with alternative RNA splicing are up-regulated in the CL subtype GBMs, and genes pertaining to energy synthesis are elevated in the NL subtype GBMs. In addition, we identified several survival-associated genes that positively correlated with glioma grades. The identified intrinsic characteristics of different GBM subtypes can offer a potential clue to the pathogenesis and possible therapeutic targets for various subtypes.

